I heard a fascinating talk yesterday by Louis Richardson of IBM. He is part of their Watson cognitive computing group. Three things stood out

a) His title – Chief Storyteller. Yes, seriously

b) Almost zero content about Watson or IBM AI successes. He talked more about human physiology and the role of cortisol, the stress hormone and oxytocin, the love and trust hormone

c) contextualized that jargon to real life human experiences. He talked about his hotel room the night before with sticky notes. Margaret Riddolls, the Westin “experience specialist” had researched his background on LinkedIn and figured he would appreciate a personalized welcome and get his oxytocin going. Louis later emailed me the picture below he had taken with her.

I posted about the talk on my Facebook page and mentioned the talk was effective for the HCM audience but likely that IT folks would have been bored. Vijay Vijaysankar of IBM responded

“When I sponsored training for my senior staff earlier, story telling was a big part of their training. And from what I hear from field - it helps equally with IT folks as well. Like my boss used to remind me - IT people are people too.”

Paul Greenberg chimed in “That is the one contemporary title I think isn't just a homage to being cutesy and a "look at how hip we are" title.” He proceeded to give examples from Adobe and SAP.

What’s going on here? It is a sea change from two decades ago when I heard Doug Burgum, then CEO of Great Plains (now part of Microsoft) use his entire keynote at the annual Stampede user event to talk about the story of an English clockmaker, John Harrison who beat out far more qualified scientists to solve one of the vexing problems of the 18th century – how to accurately measure longitudes, so important then for sailors and for all kinds of navigation since.

I had listened mouth agape to Doug’s talk. My neighbor was furious – he had come to hear about products and technical architecture, not a history lesson. Others in the audience were similarly disappointed.

Yesterday, Louis’ talk was a clear hit. People were walking around talking about oxytocin. I used my own talk to say I am a “story whisperer” – I have countless stories in the form of case studies in my books.

Story telling is the vogue. Yes, even to IT audiences. As Vijay says they are people too. We all like to sit and listen to tales around the campfire.

“Our analysis suggests that up to 30% of UK jobs could potentially be at high risk of automation by the early 2030s, lower than the US (38%) or Germany (35%), but higher than Japan (21%).”

They join the many such reports from academics, analysts and authors that filled an entire chapter titled “Sum of all Fears” in my new book, Silicon Collar. I concluded

“The reality, however, is that when Oxford, MIT, McKinsey, and Gartner talk, the person on the street and even business executives typically just read the headlines, and when all of these big brands agree on something, it solidifies readers’ overall impression—in this case, pessimism.”

The PwC analysis suffers from the same “lab rat” mindset of so many such studies. In an annex, PwC explains their approach

In the present study, we first recreated the dataset from Arntz, Gregory and Zieharn (AGZ, 2016). This comprised US data from the Programme for the International Assessment of Adult Competencies (PIAAC) database, merged with automatability data from FO. However, these sources use different occupation classifications: the 702 O*NET occupations from FO were classified using the Standard Occupational Classification (SOC) 2010 codes, whilst the PIAAC database contained occupations classified using the first 2-digits from International Standard Classification of Occupations (ISCO-08) codes.

By invoking work by “AGZ” and “FO” the study may gain credibility in the academic world. Business executives would be much more impressed if they had looked beyond supply side growth in capabilities of AI, robotics and other automation technologies. They should have gone to the demand side and validated the results with actual practitioners who would have told them about maturity and economics of automation and why they plan to continue to hire human workers for a long, long time. They could have surveyed the technology market to see who, if anybody, is developing “frankensoft” machines which have cognitive skills, limb dexterity, visual and speech capabilities and countless other skills humans bring to most jobs. They could have factored societal “circuit breakers” to automation I cataloged in this article, Slow-Motion Automation.

It’s a shame given that as a firm, PwC has access to executives across countries and industries. As a result, you get some head scratching conclusions from the PwC analysis:

- Japan is significantly less susceptible to automation than other developed countries? It is the largest robotics supplier to the world, has vending machines for literally everything, and is leading the world with robotic hotels and restaurants. It also has the most striking labor shortages with an aging population and very low immigration and therefore high incentives for automation.

- Teachers are low-risk for automation? The study explains it away as “Although the considerable growth of e-learning shows that there is scope for automation in education, this may widen access to courses rather than replacing human teachers altogether.” What e-learning promises is more just in time training. That threatens traditional school and university models. It also allows for foundational courses to be delivered as a “shared service” – virtually across schools and universities.

- The more literate a worker the lower the risk of automation? Tell that to IBM Watson, which has shown ability to consume vast amounts of medical journal information that an average doctor or surgeon cannot ever expected to keep up with. IBM is starting to call that “augmented intelligence” to supplement the capabilities of oncologists and other very “literate” occupations.

To PwC’s credit they hedge their pessimism a bit

“However, in practice, not all of these jobs may actually be automated for a variety of economic, legal and regulatory reasons.”

and

“Furthermore new automation technologies in areas like AI and robotics will both create some totally new jobs in the digital technology area and, through productivity gains, generate additional wealth and spending that will support additional jobs of existing kinds, primarily in services sectors that are less easy to automate.”

Unfortunately, what will stick from the report is the sensational conclusion that over 30% of work populations in the UK, US and Germany could be lost to automation in just over a decade.

The sad part is few of these studies, after scaring the world, come back and acknowledge they were wrong

Gartner, another former employer of mine, has projected: “By 2018, digital business will require 50% fewer business process workers.”and by that time “more than three million workers globally will be supervised by “robobosses””

We are a year away and the predictions are nowhere near likely, but what is the probability Gartner will come back and publicly say mea culpa?

MillerCoors is suing HCL for a botched SAP project. As usual there will be plenty of finger pointing and analysts saying everyone is to blame – the customer, SAP and the SI. Probably true but as in an auto accident we should be able to apportion a reasonably precise amount of blame across each of the parties.

In SAP Nation, I dedicated a whole chapter to such major failures starting in 1997. You see respected brands like Hershey, ICI, Nike and countless others mentioned in that chapter. I commented “Two decades of SAP implementation experiences would suggest that problematic projects such as those above should be slowing down, not spiking.”

What was interesting was few of those high-profile failures went to court. I found them in quarterly earnings reports, in news reports, through my work with SAP customers.

Not that I particularly want to enrich attorneys, but I wish each of these projects had been dedicated a detailed, and public, post-mortem.

We have to quit making excuses for such failures – year after year. As an industry we have to get better, much better

What scares the heck out of me is most of these relate to failed projects. There are X times more customers which did “go live” but have other “failures” – over priced application management, hosting and MPLS contracts, limited service levels, botched upgrades etc. You hardly hear about those.

For the book, I built several models of the SAP economy. I went with a $ 204 billion a year number. That was scary enough – puts the economy in the Global Top 50 GDP range of countries like Ireland and Portugal.

I did mention “I did not add amortization/write-offs to my model, with the assumption that the expense from previous years would roughly be offset by current year capitalizations. In Chapter 7, we will see a spike in public stories about SAP failures in late 2013; if that indicates a trend of increased write-offs, my model also understates that expense.”

That’s the honest truth. For a smart industry we have been fxxking up year after year, and instead of loud, public trials we have been making excuses for each other.

Michael Keaton, as Ray Kroc, looks straight into the camera in the beginning of the movie “The Founder” and makes a pitch for multi-spindle milkshake blenders. His pitch “increase supply and demand follows”. They allow a restaurant to make six thick shakes at a time. And he does it again and again. His pitch is met with cynical door shuts by restaurant owners who can barely justify a blender for one shake at a time.

Eventually, Kroc gets an order for six of the blenders. And when he calls to confirm, they increase the order to eight units. Amazed that someone would actually order so many, he drives cross-country 3,000 miles down Route 66 to California to check out the customer. He is introduced to Mac and Dick McDonald, and their innovative restaurant which brought factory concepts to the kitchen and delivered food in paper and plastic reducing need for seating space, barhops or dishwashers. Fascinated, he partners with them and eventually helps build the mighty empire which is today’s hamburger giant.

When I listen to Silicon Valley talk about AI, robotics and autonomous cars these days, I am reminded of the unsuccessful, huckster quote Keaton uses in the start of the movie. They try to sell six-spindle blenders with the promise that milk shake sales will take off. In their case, the pitch is “you will save by reducing your human workers”.

They are in love with their spindle technology. In a Twitter exchange about AI, Prof. Vivek Wadhwa who often writes and presents from a SV point of view tells me “You need to learn what exponential means, my friend. Multiple technologies are now advancing exponentially and converging.” and then he follows up with “You really don't seem to understand what exponential means. Things move slowly at first and then amaze because of curve up”

It’s all about the supply side. No mention of how much it will cost. No mention of payback. No real understanding of the customer. As I told Vivek “litmus test - call any one of 800 occupations BLS tracks and ask them when they will quit hiring humans and just use AI, robotics etc”

But instead we hear “trust us, things are so much better this time”. Sure, trust us — it’s only been 7 decades since Alan Turing defined his famous test to measure a machine’s ability to exhibit intelligent behavior equivalent to that of a human.

All the SV hype is doing is causing people to panic about jobless societies. It is leading to poor automation decisions which annoys customers and resulting revenue loss.

The reality is societies gradually absorb automation as I wrote in this column “Slow-motion automation”. As I responded to Vivek “schools you are associated with still teach regression analysis don't they? apply it to last century of automation. Gradual adoption”

And when you discuss gradual adoption, the conversation moves to symbiotic man-machine arrangements. How machines can do 3D tasks – dull, dirty, dangerous and allow humans to do those that require creativity, social skills, dexterity and so many other things our amazing bodies and minds are capable of and that customers continue to appreciate in products and services. It allows enterprises to develop “super-workers”. In my presentations, I point out that aided by telematics, UPS drivers on average get into less than one accident per million miles driven. Amazon data center employees have managed to deliver over 50 price cuts over a decade. In China, Foxconn employees working alongside bots and precision equipment have delivered billions of high-quality electronic devices to Apple and other customers.

Frankly, SV should do what Kroc did. Get in a car and drive in reverse out of CA and spend time with UPS, Amazon and others. Use their learning to help others learn how to develop their own version of “superworkers”. Quit focusing on the technology and how it is growing in speeds and feeds and look at the much bigger opportunity like Kroc did. Growth via delighted customers and super-efficient workers.

Is there a company left which has not developed smart products and services which leverage software, sensors and satellites?

I asked myself that question as I read two consecutive BusinessWeek issues with such smart products and services. Phillip Morris has been rolling out its IQOS e-cigarette for the last couple of years. It heats, not burns, tobacco so there is no hazardous smoke and tar, just tobacco-flavored vapor. The device looks like it might have been designed by Apple. Domino’s has been trying out a delivery car with special side doors and warming ovens. An independent franchisee in New Zealand is testing delivery by drone and robot. In Japan, they have tried an augmented reality app. In 2015, for the first time, more than half of Domino’s orders were placed online, and half of those came via mobile.

“(My growing book) research actually led me to a detour. I tried to find industries that were NOT thinking about smart products and services. An executive suggested I look at the portfolio of the legendary investor, Warren Buffett. He has made a fortune avoiding companies that are susceptible to technology turmoil. So, I looked at some of his investments. They include Coke, Burlington Northern, and Procter & Gamble, and found an Internet-linked vending machine, satellite-based railcar tracking, and social media innovations. They're actually very savvy technology innovators.”

For years now, pundits have said technology budgets are being taken over by the CMO. Actually, they have been taken over as much by the product side of the house. It is not unusual to find in auto makers there are more software engineers who report to product engineering/R&D than do to the CIO. It is not uncommon to see the spend with contract manufacturers like Flextronics and product design firms like IDEO exceed the spend with IT outsourcers and strategy firms. Companies are finding their spend on Build versus Buy technology has swung as they invest in proprietary code in their products. IP conversations with vendors have been overshadowed by patent and security discussions with their own customers.

More importantly the smart product/service technology is generating revenues for companies. You look at a company like GE with smart locomotives, turbines, aircraft engines and the data they are generating to allow it to talk about the Industrial Internet. And generate a new stream of digital revenues. It’s happening in every industry. When was the last time a CIO could claim that with an internal IT ERP or infrastructure project?

The path for the CIO is clear. Get more involved in the development and evolution of smart products and services. Get closer to revenue generating technology projects.

It’s not too late.

As I wrote in the book,

“So, you meet the proverbial Genie and he grants you your wish. Your product is smart now. But as the story goes—are you sure you want that wish granted? Are you ready for your new world? You are now a Technology Vendor, and that means:

_ Getting used to technology product half-lives.

_ Adjusting to Moore’s Law.

_ Rethinking product documentation.

_ Understanding technology law.

_ Getting used to competition from left field.

I issued this challenge:

“If Siemens, a company founded in 1847, Toro, founded in 1914, and Moen, founded in 1937, can do it, so can anybody else. They are not startups by a long shot. Of course there is the nightmare scenario. If our products are not viewed as smart, what about the risk from standing still? Will our customers increasingly view them as dumb?”

In my recent book, Silicon Collar, I profiled a number of examples of machine learning, cognitive computing and other evolving artificial intelligence. With growing and diverse data sets and massive computing power we have never had so much opportunity to train machines. In many ways it is an exciting time for AI.

However, I also pointed out we have had many, many false starts

“Since the 1950s! That is when Alan Turing defined his famous test to measure a machine's ability to exhibit intelligent behavior equivalent to that of a human. In 1959, we got excited when Allen Newell and his colleagues coded the General Problem Solver. In 1968, Stanley Kubrick sent our minds into overdrive with HAL in his movie, 2001: A Space Odyssey. We applauded when IBM’s Deep Blue supercomputer beat Grandmaster Garry Kasparov at chess in 1997. We were impressed in 2011 when IBM’s Watson beat human champions at Jeopardy! and again in 2016 when Google's AlphaGo showed it had mastered Go, the ancient board game. Currently, we are so excited about Amazon's Echo digital assistant/home automation hub and its ability to recognize the human voice, that we are saying a machine has finally passed the Turing Test. Almost.”

And many smart folks say we have still barely scratched the surface in terms of understanding the human mind. Yale computer science professor David Gelernter writes in his book The Tides of Mind about “the spectrum of consciousness,”. As we go down that spectrum we “prefer narrative to logic, and cross eventually into the difficult-to-remember realms of dreams.” Today’s AI is only focused on the higher areas of the spectrum he talks about.

Yann LeCun, director of AI research at Facebook, has commented, "Despite these astonishing advances, we are a long way from machines that are as intelligent as humans—or even rats. So far, we’ve seen only 5% of what AI can do."

And yet, we see a huge increase in hype about AI

Exhibit 1

IBM started marketing Watson five years before it should have. They are finally gaining some momentum, and claim by end of 2017 “we'll have a billion people touched by Watson”. So, why then confuse matters by announcing a collaboration with Einstein, the AI portion of the Salesforce platform? I read this Fortune interview with the two CEOs Ginni Rometty and Marc Benioff and I could not figure out how or why they would work together. Indeed Ginni jokes the two AI brand names make for good comedy. More ominously the partnership press release announced “IBM will deploy Salesforce Service Cloud across the company to transform its global product support services and gain a single, unified view of every IBM customer.” Is it really, truly about AI?

Exhibit 2

In researching my book I came across many technologists who claim today’s AI can do much of what CPAs, architects, even surgeons can do. But when I asked if they had looked at daily tasks and skills and attributes the jobs required, few had bothered. If they had they would have learned today’s CPA does very little book keeping, but is instead making all kinds of judgment calls about internal controls and ever changing accounting standards, counting inventories and cash balances, confirming data with third party sources among other tasks. For a machine to do all those tasks you would need a “frankensoft” with some cognitive computing skills, some robotic skills, some camera/scanning skills and drone like visualization among other attributes. Could some one put such a machine together? Sure, but at what cost? Not cheap or reliable enough otherwise accounting firms would not be hiring accounting graduates at record levels. Not just accounting, few jobs any more involve doing the same tasks over and over all day long.

Exhibit 3

Cambridge U has a “Centre for the Study of Existential Risk”. It is “dedicated to the study and mitigation of human extinction-level risks that may emerge from technological advances and human activity. “ They are spending fair amount of time thinking about risks from AI such as “automated hacking, the use of AI for targeted propaganda, the role of autonomous and semi-autonomous weapons systems, and the political challenges posed by the ownership and regulation of advanced AI systems. “ Color me cynical that AI will be that advanced any time soon. To me, the risks from pandemics, asteroid direct hits and crazy dictators require far more immediate attention.

But why blame just them? We are living in a time of AI hype. Bloomberg says mentions of AI in corporate earnings call transcripts have spiked dramatically in the last couple of years.

In this group-think about AI’s prowess, here’s what we need to watch for. Time wrote “(Yale’s) Gelernter is vastly outnumbered—so much so that he worries that his ideas might simply be ignored. ‘There has never been more arrogance and smugness’ than in today’s self-congratulatory scientific culture, he asserts.”

Personally, I would rather see modest use cases of the kind Watson is starting to show. Gradual progress is better than grandiose promises we have been making for seven decades now.

I am seeing proof points this generation of enterprise software buyer is not committing to large suites from a single vendor. There are many reasons for that as I describe in this blog post.

Having said that, the broader a vendor’s cloud, mobile or other contemporary app portfolio, the greater are the opportunities for existing and new customers to consider the vendor. That was my overwhelming reaction to the Oracle ERP cloud app summit last week as they marched through the towers in graph below (and it did not even cover their HCM or industry specific apps for which they have separate summits). And Oracle presented proof points that customers are at least buying across a couple of these product towers, and some of its tools and infrastructure, if not complete suites.

The timing was a bit awkward with their quiet period (Q3 earnings will be reported this week), but each executive crisply walked through growing feature/function sets (like revenue recognition compliance with ASC 606 and IFRS 15), expanding country support in cloud release 12 and expected deltas in 13. It was also reassuring to see each of them present new customer names which have adopted within these towers.

To me, the most interesting topics were around their Adaptive Intelligence, their Supply Chain tower and some high level discussion around innovation areas.

Adaptive Intelligence promises to use machine learning to identify patterns in first party data most ERP software has always had access to with growing third party data. Some of the outcomes Oracle is focused on include “smart offers” to customers, “best fit candidates” for HCM review, “best value freight” for logistics execs and optimized supplier payment terms for CFO prioritization. Announced six months ago at Oracle OpenWorld, this summit provided an update on progress.

The Supply Chain tower is impressively broad with blends of old Agile PLM and new like the acquired LogFire warehouse management, and aimed at customers with traditional shop floors and a growing number in advanced manufacturing (robotics, wearables etc) settings.

The innovation segments touched on Robotic Process Automation, Data Visualization and Blockchain futures. I would have liked to hear about RPA given my recent book, Silicon Collar on automation and impact on jobs, but in fairness Oracle said customers are not clamoring – yet - for many of these features.

I would have liked to hear about non-manufacturing verticals, and the Project tower section touched on some service industries, but not major ones like utilities or retail. I would also liked to hear more about the NetSuite integration post-acquisition. They touched on that but with so much to cover in the Oracle portfolio, we did not have the time.

Overall, nice to see Oracle’s growing cloud application footprint and customer adoption. It allows them to cast a wide net. I do look forward to learning how Oracle will convince customers to continue to buy large suites – now even bigger with its growing portfolio of SaaS, PaaS and IaaS

Most large vendors still talk in terms of selling entire application suites, growing their “wallet share” of customer IT spend, and the joy of their “all you can eat” buffets. It all sounds so retro, 90s talk because so many customers, especially those in middle of significant digital transformations are more into buying small components, building their own applications and integrating.

Many reasons for the disconnect between vendor and customer talk:

a) The last generation of vendor suites disappointed. For all the talk of “wall to wall” functionality, customers ended up buying number of “ring fence” applications and customizing the packages as vendors did not adequately keep up with changes in their industries and regulatory requirements . In SAP Nation, I pointed out “According to Panaya, a tool vendor, "More than 50% of SAP shops have 40+ satellite applications. Of these less than 10 are SAP applications." CAST Research Labs has analyzed customizations at several major SAP customers and found most of the customizations were sizable, with many of them high-risk according to its benchmarks.”

b) The concentration of dollars with a handful of suppliers led to “lock-in” and bad vendor behavior. It is rare to find a CIO who will not share a story of an unjustified vendor audit or other aggressive behavior. The promise of economies from vendor reduction and concentration has mostly stayed just a promise. It’s hardly an endorsement to sign up again for procurement of large suites.

c) As they rethink business processes and especially business models as part of their digital transformations, enterprises are finding a wide array of cloud applications, easily developed mobile and analytical applications and a growing array of automation technologies (with AI, robotics, wearables etc) that they can themselves weave together. In contrast they find enterprise vendors are mostly taking old processes and “moving them to the cloud”. As one CIO told me “Our industry has gone through so many changes in last decade that you are almost better off starting from scratch.” Said another “there is not much original thinking. Enterprise UX continues to trail consumer tech UX. Still a keyboard and mouse paradigm when we should have much more voice driven and automated processes“

One of the biggest constraints to moving aggressively to a build versus buy paradigm is most CIOs have very lean staffing models – few architects, few developers or integration specialists. As they committed to the last generation of suites they also moved to a different staffing model, often heavily outsourced. That will not change overnight – but that hardly makes them welcome a new generation of suites.

In the wake of all accentuated concern in SAP world about the “indirect access” clause, Geoff Scott, Chairman of the America’s SAP User Group says

“I know personally that SAP isn’t interested in pursuing court action to resolve these conversations and would like to have a dialogue with customers on the topic, which is why these conversations are so important.

Look for a lot more from ASUG. ASUG advocating on these topics is what drives the value in being a member. And ASUG needs to hear your voice.”

We are in 2017. If I was a member I would ask Geoff why ASUG not been advocating aggressively for its users on this topic for a decade now? Why only now?

When I shared an early copy of SAP Nation with him in 2013, I asked him a similar question. How come ASUG has not been highlighting the massive cost of the SAP ecosystem to customers?

In fairness, it’s not just Geoff. Other user groups are just as passive. They are more focused on events and training sessions, not customer advocacy.

Indeed as I noted in SAP Nation, other market watchers have been just as passive – analysts, academia, regulators.

I concluded

“Many customer executives will say they have little time or interest to “influence the influencers” discussed above. You cannot blame them, but then they need to increase their own oversight and help protect their own interests.”